The Quantitative Model Organism Proteomics (Q-MOP) Initiative was launched in October 2009 (see also News & Events) as successor of the Center for Model Organism Proteomes (C-MOP), an inter-disciplinary project with the
as the leading institution. It is part of the University Research Priority Program Systems Biology/Functional Genomics.
The main objective of this initiative is the implementation, further development and application of advanced targeted quantitative
proteomics workflows that allow researchers to study hypothesis-driven research questions in a systems biology context and to capitalize on the differentiating advantages of direct protein profiling over other technologies.
In a first discovery phase, C-MOP has comprehensively described the proteomes of a number of model organisms of high relevance for experimental biology: Arabidopsis thaliana, Caenorhabditis elegans and Drososphila melanogaster. Results of this first phase include generation of the most extensive proteomics datasets for these model organisms. These results have spurred the development of novel proteomics technologies and bioinformatics data analysis approaches, as well as the improvement of the genome annotation of these organisms.
Schematic overview of factors relevant for the generation of proteome catalogs. Technological developments play a central role to enable researchers to generate complete quantitative datasets,
currently of small systems like a signaling pathway, and in the future even of entire proteomes. Figure reproduced with permission from http://dx.doi.org/10.1016/j.jprot.2009.12.007.
In a second scoring phase, the focus of Q-MOP is now shifting towards the application of advanced targeted quantitative workflows capable of providing complete quantitative proteomics
datasets. Proteins of interest can be detected with a much increased sensitivity and at a higher throughput. These improved proteomics technologies will enable researchers
to address fundamental biological problems in a systems biology context.
A selection of targeted quantitative proteomics applications relying on
proteotypic peptides (PTPs), i.e. signature peptides that unambiguously
identify one protein and that are observable by mass spectrometry.